Bibliographic record
Abstract
This article focuses on Mexican individuals who grew up in the U.S. (1.5 generation) without documents and were not able to benefit from Deferred Action for Childhood Arrivals (DACA) or who were unable to renew their DACA. A 2012 Executive Action by former president Obama, DACA gave some undocumented youth relief from deportation and a 2-year renewable work permit provided they met certain criteria. Undocumented individuals DACA failed to reach have generally been overlooked in immigration research in favor of examining how DACA recipients' lives have been transformed by DACA. This project helps fill this gap by examining life outside of DACA, and how the program acted as an internal U.S. border of exclusion for many. This research also aids in understanding the impacts of changing government policies on vulnerable populations, especially those who are in some respects made even more vulnerable by their faith in the government, fear of the government, or are actively excluded from government programs. This investigation is part of a study that compares 20 DACA beneficiaries to 20 individuals without DACA. Through ethnographic methodologies and one-on-one interviews, this article examines the 20 research participants who fall outside DACA. It investigates why people who qualified for DACA did not apply, barriers to applying/renewing, and how members of the 1.5 generation were excluded from the program by restrictions such as date of arrival requirements. The article discusses what it means for research participants to live outside of DACA, and how they see their lives because they do not have DACA while others do. For example, what does it mean to age out of qualifying for DACA? What actions did individuals then take regarding their lack of legal status?
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".